Despite the recent advances in Deep Learning, it is still very difficult to apply machine learning to real-world industry scenarios.
This is partly because building a Deep Learning system requires extreme amounts of annotated or labeled data that involves labor-intensive manual work,
and also because a stand-alone AI system is yet to be fully trusted.
Manual data labeling can cost enormous amount of resources in terms of both time and money,
and an overly trusted AI system could lead to system malfunction and even fatal accidents.
We want to solve these two problems and lower the hurdle for various industries to adopt machine learning technology.
Our Mission — "Democratize AI"
Currently, only a handful of companies with enough data and expertise in machine learning can utilize the full potentials of state-of-the-art AI technology.
However, we believe that AI should be widely adopted and be used as a commodity across all industries to truly empower human and revolutionize our lives.
To achieve this mission, we develop Human-in-the-Loop AI technology that enables AI and humans to assist and collaborate with each other.
AI and humans are naturally adept at different tasks, and we harness the best of both worlds — algorithms automate laborious but repetitive tasks
and human workers collaborate with and verify the works of algorithms. With this technology, we first semi-automate the data annotation process and
ultimately serve various industries with AI systems that effectively collaborate with on-site human experts.